T1 and T2 quantification have previously been used in some clinical diagnoses (e.g., evaluation of musculoskeletal cartilage, evaluation of cardiac function) with some success. Unlike conventional qualitative image-based approaches, a quantification based diagnosis relies on objective relaxation parameter quantification. Conventional magnetic resonance imaging (MRI) is typically configured to produce qualitative data useful for providing qualitative results (e.g., images) with various weightings or contrasts that highlight a particular parameter (e.g., T1 relaxation, T2 relaxation). This conventional approach is constrained by the fact that conventional MRI is focused mainly on producing qualitative images. Constraining nuclear magnetic resonance (NMR) to techniques that facilitate producing images may not be appropriate in some cases. For example, an image based approach may not be appropriate when a goal for an NMR inquiry is to make a diagnosis based on quantified relaxation parameters. Instead, quantitative results that can be acquired more quickly may be sufficient and/or desired.
A conventional MRI acquisition involves numerous repetitions of prepare/wait/acquire pulse sequences. For example, a first pulse sequence may be applied a large number of times to acquire T1 weighted signals for all voxels in a volume of interest (Rol) and then a second pulse sequence may be applied a large number of times to acquire T2 weighted signals for all the voxels in the Rol. Registering (e.g., aligning) the signals from these two acquisitions to make a readable image may be difficult. Regardless of how lengthy and how difficult the process, given enough time, this repetitive application of prepare/wait/acquire pulse sequences can produce excellent and valuable images from which a diagnosis can be made.
Conventional images produced by conventional systems are typically viewed by a radiologist and/or surgeon who interprets the qualitative images for specific condition and/or disease signatures. Diagnosis may involve examining multiple image types (e.g., T1-weighted, T2-weighted) acquired in multiple imaging planes. Making a diagnosis by examining qualitative images may require particular skill to be able to assess changes from session to session, from machine to machine, and from machine configuration to machine configuration. Thus, qualitative images are only as good as the image interpreter and all image based (e.g., qualitative) diagnoses end up being subjective. Diagnoses based on qualitative images also depend on the availability of a skilled and/or certified person to make the diagnosis. This may be a challenge in certain environments. For example, while some rural or remote facilities may be able to house an MRI apparatus, there may be no radiologist available to examine the images acquired.
Although conventional MRI has served the clinical community well for many years, in some cases objectivity may be desired over subjectivity, and automation may be desired over in-person diagnosis. Thus, T1, T2, spin density, off-resonance, diffusion weighted, and other relaxation parameter quantifications have recently become more relevant due, for example, to the availability of new techniques and new pulse sequences. Unfortunately, in a quantitative approach, even a slight system imperfection may yield a substantial impact on quantified mapping values. While this impact may not be apparent on qualitative images and may not affect conventional qualitative diagnosis, the impact on quantification based diagnoses may be significant.
Due to ongoing technical limitations, system performance is typically imperfect at some level. In particular, for multi-echo readouts, radio frequency (RF) imperfections may introduce echo signal errors due, for example, to an imperfect slice profile. By way of illustration, the second echo signal in a multi-echo readout may be too high due to the stimulated echo effect. Additionally, the stimulated echo effect may impact more than just the second echo signal, particularly for species with long relaxation times.